Purpose: Graphics Processing Unit (GPU) has become increasingly important in radiotherapy. However, it is still difficult for general clinical researchers to access GPU codes developed by other researchers with GPU expertise, and also for developers to benchmark their codes. It is quite often to see repeated efforts spent on developing GPU codes with low quality. The goal of this project is to establish an infrastructure for sharing GPU codes in the community.

Methods: We deployed a GPU code sharing infrastructure on a GPU cluster. A number of codes developed in our group can be accessed via a web interface. To use the services, researchers first upload their test data or use the data provided by our system. Then they have to select the GPU device they are going to run the codes. Our system offers all mainstream GPU hardware for code benchmarking purpose. After the code running is complete, the system will automatically summarize and display the computing results. We will also release a SDK to allow the developers to build their own algorithm implementation and submit their binary codes to the system. The submitted code will be systematically benchmarked using a variety of GPU hardware and representative clinical data provided by our system.

Results: This project provides a platform to the public to access a variety of GPU codes for radiotherapy research via a web interface. With the help of this platform, researchers are able to focus their efforts on clinical research. Developers will also benefit from this platform by benchmarking their codes on various GPU platforms and clinical data sets and comparing with other people's codes for the same application.

Conclusion: The gateway for GPU code developers and clinical research users can greatly facilitate the adoption of GPU codes in radiotherapy.